**********************************************************************************************
* Reproduces Table 1
*
* Ajzenman, Elacqua, Jaimovich and Pérez-Núñez (2024)."Humans versus Chatbots: Scaling-up behavioral interventions to reduce teacher shortages"  	  		
*
**********************************************************************************************

matrix drop _all
mat D=J(13,5,.)
local i= 1
 
 *Baseline covariates summary statistics
foreach var in sexo municipal subvencionado particular top_30 agno_egreso prom_notas ptje_ranking prom_cm_actual padres_incompleta padres_media_completa padres_superior bajo_linea_pobreza{
sum `var' 
mat D[`i',1]= r(N)
mat D[`i',2]= r(mean)
mat D[`i',3]= r(sd)
mat D[`i',4]= r(min)
mat D[`i',5]= r(max)
local i =`i'+1
}


mat rownames D= "Female" "Public" "Private-Subsidized" "Private"  "High school GPA, top 30%" "Recent year graduation"  "High school GPA" "High school ranking score" "Average math and verbal test" "Parents without high school" "Parents with high school " "Parents with higher education" "Low income family"

mat colnames D= "Obs" "Mean" "Std. Dev." "Min"  "Max"

matlist D

frmttable using "${output}/Table1.tex", statmat(D) varlabels replace sdec(0,3,3,0,0,0) tex fr
